The proliferation of the World Wide Web, and, more recently, the ability to view information from the Web using wireless, hand-held devices, has significantly increased consumers' ability to access the Web from almost anywhere. Consumers use these devices to view and interact with content such as general news, sports, and business, as well as use the devices to create user-generated content through social media sites, photo-sharing sites, and others. Consumers also are increasingly using their devices for transactional purposes—buying movie tickets, paying for meals, or purchasing goods and services. Essentially, mobile, Web-enabled smart-phones, tablets and similar devices have taken the place of the desktop computer, telephone, and credit card as the advertising platform and point-of-sale of choice.
This presents a bit of a challenge for advertisers, ad networks, content providers, and other members of the so-called “advertising ecosystem.” In the past, advertisers relied on certain known data about consumers—whether it be personal information provided by the consumer, data representing prior interactions with an online retail store, or data collected as the consumer navigated across the Web. All of this data was easily available and could be tied directly to a person, and, if the individual provided additional data, could be combined with demographic data, thus building a particular user profile. This resulted in more effective ad targeting.
Providing targeted ads has been beneficial to both the advertiser and the consumer. For example, in an advertising context, both the advertiser and the consumer benefit from targeted ads; the consumer receives ads that are relevant to his or her interests and the advertiser gets improved response to those targeted ads (e.g., a higher “lift”). But, as described above, in order to provide targeted content, the provider must both possess and effectively utilize information about the recipient; and further, the provider must also possess and effectively utilize information about the content that is being delivered. This is a challenge when delivering ads to mobile devices.
Certain mobile software applications and websites provide interactive advertisement slots of various formats. Typically, an advertisement request is sent from the mobile device directly or indirectly to one or more ad servers, e.g., when the user's mobile device browser or application requests an ad from an ad server, or a publisher system makes such a request on behalf of the user. In some cases, intermediate advertising networks may manage the allocation of advertising content to advertising slots (sometimes referred to as “inventory”) based on economic and other terms. The advertisement request may contain a suite of information fields such as a unique identifier call device ID, the time when request is initiated, and the geo-location of the device initiating the request. From those fields, additional information can be derived, for example, the local time when the request is initiated. The ad server (or ad network) makes a real-time decision on ad serving based on information contained in the ad request.
Demographically targeted advertising has been instrumental in improving the efficiency of advertising campaigns. For example, market research firms gather and analyze data regarding consumers, products, purchase histories, survey results, and other information to define marketing segments, sometimes even at the household level. For example, a list of households may be created that identifies families that are likely to purchase a certain type of car, and the automobile company may send mailings to this segmented list in an attempt to sell more cars. This approach does not translate well into the mobile advertising space, however. First, advertising companies do not have access to mobile subscriber data, as the network providers do not share address and personal data associated with a particular number or device. Second, the mobile device moves among various locales over time and cannot be immediately associated to a particular household.
Mobile display advertising has become an area of huge growth in recent years. While the advertising volume delivered via mobile devices has increased drastically, overall mobile advertising revenue continues to lag due in part to lack of effective targeting. One of the biggest challenges for advertisers and publishers on the mobile advertising platforms is that they are not able to identify content requests that come from members of their “target” audience. There are two primary reasons for this shortfall. First, while many brands and advertisers have access to the registration and purchase history information they collect about their customers, they have no way to associate mobile users with various demographic and audience segments. Second, while many third party data aggregation and analytics companies collect consumers' purchase behavior and other information at a household level, they do not know which mobile devices belong to a particular household.
Therefore, there is a need for a comprehensive platform that can bring together consumers' online and offline purchase behavior and demographic data to build audience segments, and tie mobile devices to the segments such that ads can be delivered to mobile devices that belong to the households identified as high-lift segments.